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All Journal Jurnal Pengabdian kepada Masyarakat Nusantara Journal of Soft Computing Exploration SENTRI: Jurnal Riset Ilmiah Jurnal Cakrawala Maritim
Pujiputra, Anggarjuna Puncak
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Aerospace Engineering Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

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Implementation of integrated temperature, humidity, and dust monitoring system on building electrical panel Khumaidi, Agus; Hasin, Muhammad Khoirul; Pujiputra, Anggarjuna Puncak; Irsyad, Sholahuddin Muhammad; Rinanto, Noorman; Rachman, Isa; Budi, Perdinan Setia; Malik, Alfianto Taufiqul; Bayu, Nurissabiqoh Binta
Journal of Soft Computing Exploration Vol. 5 No. 4 (2024): December 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i4.483

Abstract

This research aims to develop and implement an electrical power monitoring system at the Sub Sub Distribution Panel (SSDP) in the Building. The system is designed to monitor power usage in real-time, provide accurate information on energy consumption, and detect potential energy waste. The methodology used includes hardware and software design. The hardware consists of current and voltage sensors connected to a microcontroller. The data collected by the sensors is then transmitted via Wi-Fi network to the server for analysis. The software uses an Internet of Things (IoT) platform that displays the data in the form of graphs and tables. The implementation shows that the system is capable of monitoring power usage with a high degree of accuracy. The sensors used, namely PM2100 for voltage, SHT20 for temperature and humidity, and GP2Y101AU0F for dust concentration, proved effective in generating accurate real-time data. Based on the test results, the voltage measurement error with the PM2100 was only 0.035%, while the current measurement resulted in an error of 0.48%. The SHT20 sensor recorded an error of 2.4% for temperature and 1.0% for humidity. Dust measurements with the GP2Y101AU0F sensor had a very small error of 0.02%. These results indicate that the tested device has a sufficient level of precision for electrical power and environmental monitoring applications.
Green Action sebagai Upaya Rehabilitasi Ekosistem Mangrove di Kelurahan Romokalisari, Surabaya Alwi, Alwi Sina Khaqiqi; Rahayuningsih, Siti; Al Hazman, Muhammad; Widyastuti, Indri ika; Sholikah, Evi Nafiatus; Gastriani, Ovi Prina; Wibowo, Sekarsari; Nisazarifa, Adristi; Pujiputra, Anggarjuna Puncak; Sukarno, Friska Intan; Brian, Thomas; Parman
Jurnal Cakrawala Maritim Vol. 8 No. 2 (2025): Jurnal Cakrawala Maritim
Publisher : P3M Politeknik Perkapalan Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35991/jcm.v8i2.40

Abstract

Mangroves have several functions, including maintaining biological balance in coastal ecosystems and tourism. On the other hand, mangroves are also very vulnerable to natural disturbances, anthropogenic, land conversion, and even pollution from various human activities. The success of mangrove planting activities does not only depend on the selection of the type of mangrove to be planted, but also on the selection of a suitable location to support its growth. Mangroves in Romokalisari Village, Surabaya are currently still relatively few. This needs to be planted because the mangroves function as wave breakers and tourist attractions. Mangrove planting activities in Romokalisari Village, Surabaya, were carried out by residents, lecturers and students of the Surabaya State Polytechnic of Shipping. The results of the mangrove planting are expected to have a positive impact on Romokalisari Village, Surabaya and its surroundings.
Penyuluhan Budidaya Perairan Terhadap Masyarakat Tanjung Tembaga Probolinggo untuk Mendorong Transformasi Ekonomi Biru Sukarno, Friska Intan; Widyastuti, Indri Ika; Wibowo, Sekarsari; Brian, Thomas; Pujiputra, Anggarjuna Puncak; Pratama , Moh. Andris; Rahayu, Putri Nur
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 6 No. 2 (2025): Jurnal Pengabdian kepada Masyarakat Nusantara Edisi April - Juni
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v6i2.6199

Abstract

Nelayan pada umumnya menggantungkan aktivitas ekonominya pada sumber daya laut dan pesisir melalui penangkapan ikan secara langsung, namun cara yang digunakan cenderung tidak efektif dan sangat bergantung pada kondisi cuaca, sehingga hasil tangkapan menjadi tidak stabil.  Metode yang digunakan meliputi penyuluhan, diskusi partisipatif, dan evaluasi melalui survei serta wawancara kepada nelayan peserta kegiatan. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pengetahuan dan kesadaran masyarakat pesisir Tanjung Tembaga, Kota Probolinggo, mengenai alternatif usaha perikanan yaitu budidaya laut. Permasalahan yang dihadapi nelayan lokal saat ini adalah ketergantungan terhadap hasil tangkapan yang cenderung menurun akibat overfishing dan perubahan iklim. Hasil kegiatan menunjukkan bahwa 82% peserta memperoleh pemahaman baru tentang budidaya perairan berbasis Keramba jaring apung, dan 90% menyatakan ketertarikan untuk mencoba usaha tersebut.  Kegiatan ini juga berhasil mengubah persepsi masyarakat terhadap potensi ekonomi budidaya laut dan meningkatkan keterlibatan dalam pengelolaan sumber daya pesisir secara berkelanjutan. Dengan demikian, program ini memberikan dampak positif dalam mendorong transformasi ekonomi biru melalui peningkatan kapasitas dan kemandirian nelayan lokal.
Segmentasi Citra Pengelasan Kapal Menggunakan Convolutional Neural Network Brian, Thomas; Pujiputra, Anggarjuna Puncak; Putri Nur Rahayu; Augustino, Immanuel Freddy; Parman, Parman; Bone, Iskia Ipan Dua’
SENTRI: Jurnal Riset Ilmiah Vol. 4 No. 10 (2025): SENTRI : Jurnal Riset Ilmiah, Oktober 2025
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/sentri.v4i10.4767

Abstract

Welding inspection plays a critical role in the shipbuilding industry to ensure the integrity and quality of welded joints. However, the prevailing manual inspection procedures are inherently subjective, prone to bias, and result in inconsistent quality assessments. Therefore, there is a strong need for an automated and intelligent system capable of objectively detecting welding points. To address this, we propose an advanced segmentation model based on deep learning and computer vision techniques, specifically utilizing the enhanced Nested UNet architecture with extensive architectural modifications and comprehensive hyperparameter tuning. To further optimize the segmentation performance, we systematically compare different convolutional blocks integrated into the network architecture. The dataset used consists of 548 welding images. Each image is manually annotated using the VGG Image Annotator (VIA) application by marking the weld point areas as polygons. This research focuses on the development of a Nested UNet model, a deep learning-based image segmentation model for detecting weld points from previous models using the UNet architecture. During the training process, performance on both the training and validation datasets is continuously monitored and recorded. This results in several logs recording the training loss, validation loss, training IoU, and validation IoU for each of the three types of convolutional blocks used in the dense bottleneck. Our experimental evaluation shows that the use of VGG - Dense - VGG convolutional blocks in Nested UNet yields the highest performance, achieving a Training Dice score of 0.92970 and a Validation Dice score of 0.89695 on our collected dataset.
Co-Authors Agus Khumaidi Al Hazman, Muhammad Alwi Sina Khaqiqi Augustino, Immanuel Freddy Bayu, Nurissabiqoh Binta Bone, Iskia Ipan Dua’ Brian, Thomas Budi, Perdinan Setia Gastriani, Ovi Prina Hasin, Muhammad Khoirul Malik, Alfianto Taufiqul Nisazarifa, Adristi Parman parman parman Pratama , Moh. Andris Putri Nur Rahayu Rahayu, Putri Nur Rahayuningsih, Siti Rinanto, Noorman Sholahuddin Muhammad Irsyad Sholikah, Evi Nafiatus Sukarno, Friska Intan Wibowo, Sekarsari Widyastuti, Indri Ika